Repository Analysis

zilliztech/claude-context

Code search MCP for Claude Code. Make entire codebase the context for any coding agent.

4.7 Likely human-written View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of zilliztech/claude-context, a TypeScript project with 12,130 GitHub stars. SynthScan v2.0 examined 34,005 lines of code across 136 source files, recording 115 pattern matches distributed across 14 syntactic categories. The overall adjusted score of 4.7 places this repository in the Likely human-written band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

4.7
Adjusted Score
4.7
Raw Score
100%
Time Factor
2026-07-14
Last Push
12.1K
Stars
TypeScript
Language
34.0K
Lines of Code
136
Files
115
Pattern Hits
2026-07-14
Scan Date
0.01
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

This chart maps the temporal evolution of the adjusted synthetic code score across successive scan runs. An upward trajectory indicates ongoing incorporation of AI-generated code or expanding LLM-assisted scaffolding; a stable or declining trajectory may reflect active human refactoring, code removal, or the adoption of stricter authorship policies. The dashed secondary line (right axis) independently tracks total raw pattern hit count, which can diverge from the normalised score when codebase size changes significantly between scans.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 1MEDIUM 12LOW 102

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 115 distinct pattern matches across 14 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Structural Annotation Overuse19 hits · 33 pts
SeverityFileLineSnippetContext
LOWdocs/troubleshooting/troubleshooting-guide.md10### Step 1: Check Indexing Status FirstCOMMENT
LOWdocs/troubleshooting/troubleshooting-guide.md22### Step 2: Get Debug LogsCOMMENT
LOWdocs/troubleshooting/troubleshooting-guide.md44### Step 3: Reconnect MCP Server After Configuration ChangesCOMMENT
LOWdocs/troubleshooting/troubleshooting-guide.md64### Step 4: Search Documentation and CommunityCOMMENT
LOWdocs/troubleshooting/troubleshooting-guide.md79### Step 5: Report the IssueCOMMENT
LOWdocs/troubleshooting/troubleshooting-guide.md83### Step 6: After Version UpdatesCOMMENT
LOWdocs/troubleshooting/troubleshooting-guide.md96### Step 1: Get Debug LogsCOMMENT
LOWdocs/troubleshooting/troubleshooting-guide.md107### Step 2: Search Documentation and CommunityCOMMENT
LOWdocs/troubleshooting/troubleshooting-guide.md122### Step 3: Report the IssueCOMMENT
LOWdocs/troubleshooting/troubleshooting-guide.md126### Step 4: After Version UpdatesCOMMENT
LOWdocs/getting-started/quick-start.md7### Step 1: Get API KeysCOMMENT
LOWdocs/getting-started/quick-start.md15### Step 2: Configure Claude CodeCOMMENT
LOWdocs/getting-started/quick-start.md29### Step 3: Start Using Claude ContextCOMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts256 // Step 1: Create collection with schemaCOMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts259 // Step 2: Create index for vector field (separate API call)COMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts262 // Step 3: Load collection to memory for searchingCOMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts606 // Step 1: Create collection with schema and functionsCOMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts609 // Step 2: Create indexes for both vector fieldsCOMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts612 // Step 3: Load collection to memory for searchingCOMMENT
Self-Referential Comments7 hits · 19 pts
SeverityFileLineSnippetContext
MEDIUMevaluation/analyze_and_plot_mcp_efficiency.py367 # Create the efficiency chartCOMMENT
MEDIUMevaluation/generate_subset_json.py50 # Create the JSON structure that _prepare_instances expectsCOMMENT
MEDIUMevaluation/retrieval/custom.py126 # Create the appropriate context manager based on which sessions we needCOMMENT
MEDIUMevaluation/retrieval/base.py55 # Create a simple dict that mimics HuggingFace dataset structureSTRING
MEDIUMevaluation/servers/edit_server.py10# Create the MCP serverCOMMENT
MEDIUMevaluation/servers/read_server.py15# Create the MCP serverCOMMENT
MEDIUMevaluation/servers/grep_server.py16# Create the MCP serverCOMMENT
Deep Nesting18 hits · 18 pts
SeverityFileLineSnippetContext
LOWpython/test_endtoend.py17CODE
LOWpython/ts_executor.py26CODE
LOWevaluation/analyze_and_plot_mcp_efficiency.py54CODE
LOWevaluation/utils/format.py6CODE
LOWevaluation/utils/format.py25CODE
LOWevaluation/utils/format.py108CODE
LOWevaluation/utils/format.py262CODE
LOWevaluation/utils/format.py349CODE
LOWevaluation/utils/file_management.py13CODE
LOWevaluation/utils/llm_factory.py7CODE
LOWevaluation/retrieval/custom.py293CODE
LOWevaluation/retrieval/base.py42CODE
LOWevaluation/retrieval/base.py126CODE
LOWevaluation/servers/read_server.py20CODE
LOWevaluation/servers/read_server.py137CODE
LOWevaluation/servers/read_server.py186CODE
LOWevaluation/servers/read_server.py211CODE
LOWevaluation/servers/grep_server.py36CODE
Hyper-Verbose Identifiers18 hits · 18 pts
SeverityFileLineSnippetContext
LOWpython/test_endtoend.py17def run_context_endtoend_test():CODE
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts37async function createCollectionWithLimitCheck(CODE
LOWpackages/chrome-extension/src/background.ts403async function handleTestMilvusConnection(sendResponse: Function) {CODE
LOWpackages/mcp/src/splitter.ts9export function resolveRequestSplitterType(splitterType: unknown): RequestSplitterType {CODE
LOWpackages/mcp/src/config.ts84export function getDefaultModelForProvider(provider: string): string {CODE
LOWpackages/mcp/src/config.ts102export function getEmbeddingModelForProvider(provider: string): string {CODE
LOWpackages/mcp/src/config.ts121function getPositiveIntegerFromEnv(name: string): number | undefined {CODE
LOWpackages/mcp/src/sync.ts41function getBackgroundSyncIntervalMs(): number {CODE
LOWpackages/vscode-extension/src/extension.ts184function reloadContextConfiguration() {CODE
LOWevaluation/utils/format.py25def extract_file_paths_from_edits(response, codebase_path):CODE
LOWevaluation/utils/format.py77def _normalize_to_relative_path(file_path, codebase_path):CODE
LOWevaluation/utils/format.py94def extract_oracle_files_from_patch(patch):CODE
LOWevaluation/utils/format.py108def extract_edit_calls_from_conversation_log(log_content: str):CODE
LOWevaluation/utils/format.py177def find_line_number_for_old_string(file_path: str, old_string: str):CODE
LOWevaluation/utils/format.py349def extract_conversation_summary(response):CODE
LOWevaluation/utils/format.py443def print_conversation_summary(response):CODE
LOWevaluation/retrieval/custom.py183 async def _load_tools_from_sessions(self, sessions: Dict):CODE
LOWevaluation/retrieval/base.py126 def _filter_existing_instances(STRING
Excessive Try-Catch Wrapping17 hits · 17 pts
SeverityFileLineSnippetContext
MEDIUMpython/test_endtoend.py94 print(f"Error: {result.get('error')}")CODE
LOWpython/test_endtoend.py99 except Exception as e:CODE
LOWpython/ts_executor.py122 except Exception as e:CODE
LOWpython/ts_executor.py302 except Exception as e:STRING
MEDIUMpython/ts_executor.py303 print(f"Error: {e}")STRING
LOWevaluation/analyze_and_plot_mcp_efficiency.py102 except Exception as e:CODE
LOWevaluation/utils/format.py191 except Exception:CODE
LOWevaluation/utils/file_management.py95 except Exception as e:CODE
LOWevaluation/retrieval/custom.py279 except Exception as e:CODE
LOWevaluation/retrieval/custom.py318 except Exception as clear_error:CODE
LOWevaluation/retrieval/custom.py381 except Exception as e:CODE
LOWevaluation/retrieval/custom.py390 except Exception as e:CODE
LOWevaluation/retrieval/base.py207 except Exception as e:STRING
LOWevaluation/servers/read_server.py132 except Exception as e:CODE
LOWevaluation/servers/read_server.py181 except Exception as e:CODE
LOWevaluation/servers/read_server.py266 except Exception as e:CODE
LOWevaluation/servers/grep_server.py211 except Exception as e:CODE
Redundant / Tautological Comments13 hits · 16 pts
SeverityFileLineSnippetContext
LOWpython/test_endtoend.py48 # Output resultsCOMMENT
LOWevaluation/generate_subset_json.py44 # Check if it matches our criteriaCOMMENT
LOWevaluation/utils/format.py126 # Check if the line contains complete argumentsCOMMENT
LOWevaluation/retrieval/base.py44 # Check if it's a JSON fileSTRING
LOWevaluation/retrieval/base.py109 # Check if we've already processed enough instancesSTRING
LOWevaluation/retrieval/base.py153 # Check if output directory exists and has subdirectories with result.jsonSTRING
LOWevaluation/servers/read_server.py42 # Check if file existsCOMMENT
LOWevaluation/servers/read_server.py46 # Check if it's actually a fileCOMMENT
LOWevaluation/servers/read_server.py153 # Check if directory existsCOMMENT
LOWevaluation/servers/read_server.py157 # Check if it's actually a directoryCOMMENT
LOWevaluation/servers/read_server.py203 # Check if directory existsCOMMENT
LOWevaluation/servers/read_server.py207 # Check if it's actually a directoryCOMMENT
LOWevaluation/servers/grep_server.py57 # Check if we're in a git repository and try git grep firstCOMMENT
Verbosity Indicators6 hits · 14 pts
SeverityFileLineSnippetContext
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts256 // Step 1: Create collection with schemaCOMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts259 // Step 2: Create index for vector field (separate API call)COMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts262 // Step 3: Load collection to memory for searchingCOMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts606 // Step 1: Create collection with schema and functionsCOMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts609 // Step 2: Create indexes for both vector fieldsCOMMENT
LOWpackages/core/src/vectordb/milvus-restful-vectordb.ts612 // Step 3: Load collection to memory for searchingCOMMENT
Modern AI Meta-Vocabulary3 hits · 9 pts
SeverityFileLineSnippetContext
MEDIUMpackages/mcp/README.md50# Optional: Specify embedding model (default: text-embedding-3-small)COMMENT
MEDIUMpackages/mcp/README.md78# Optional: Specify embedding model (default: voyage-code-3)COMMENT
MEDIUMpackages/mcp/README.md103# Optional: Specify embedding model (default: gemini-embedding-001; supports gemini-embedding-2)COMMENT
Unused Imports6 hits · 6 pts
SeverityFileLineSnippetContext
LOWpython/ts_executor.py11CODE
LOWevaluation/analyze_and_plot_mcp_efficiency.py13CODE
LOWevaluation/run_evaluation.py6CODE
LOWevaluation/utils/format.py1CODE
LOWevaluation/retrieval/custom.py14CODE
LOWevaluation/servers/edit_server.py7CODE
Magic Placeholder Names1 hit · 5 pts
SeverityFileLineSnippetContext
HIGHpackages/mcp/package.json18 "start:with-env": "OPENAI_API_KEY=${OPENAI_API_KEY:your-api-key-here} MILVUS_ADDRESS=${MILVUS_ADDRESS:localhost:CODE
Modern Structural Boilerplate4 hits · 4 pts
SeverityFileLineSnippetContext
LOWevaluation/run_evaluation.py11logger = logging.getLogger(__name__)CODE
LOWevaluation/utils/file_management.py10logger = logging.getLogger(__name__)CODE
LOWevaluation/retrieval/custom.py23logger = logging.getLogger(__name__)CODE
LOWevaluation/retrieval/base.py18logger = logging.getLogger(__name__)CODE
Overly Generic Function Names1 hit · 1 pts
SeverityFileLineSnippetContext
LOWpython/ts_executor.py234export async function processData(data: any[]): Promise<{ count: number; items: any[] }> {CODE
Over-Commented Block1 hit · 1 pts
SeverityFileLineSnippetContext
LOWpackages/chrome-extension/src/vm-stub.js1// This file is intentionally left blank to act as a stub for the 'vm' module in the browser environment. COMMENT
Example Usage Blocks1 hit · 0 pts
SeverityFileLineSnippetContext
LOWpython/ts_executor.py220# Usage exampleSTRING